Toward Individualized Atherosclerosis Therapy: Clinical Endotypes, Programmable Therapeutics, and Delivery Constraints
TL;DR
This work proposes an executable framework for individualized atherosclerosis therapy that organizes clinical decision‐making around three axes: actionable endotype identification, selection of a matched therapeutic modality, and evaluation of delivery feasibility.
Abstract
Atherosclerosis remains the dominant substrate of atherosclerotic cardiovascular disease (ASCVD), yet recurrent events persist even when LDL cholesterol is driven to guideline targets, underscoring residual risk as a central limitation of contemporary prevention. This residual risk is not monolithic: It reflects mechanistically distinct drivers, including lesion‐level structural differences, inflammation amplified by clonal hematopoiesis of indeterminate potential (CHIP), and genetically anchored lipoprotein liabilities that conventional lipid lowering does not adequately modify. We propose an executable framework for individualized atherosclerosis therapy that organizes clinical decision‐making around three axes: actionable endotype identification, selection of a matched therapeutic modality, and evaluation of delivery feasibility. Programmable medicines, particularly liver‐directed siRNA and antisense oligonucleotides, have expanded what is therapeutically reachable for hepatic targets, whereas gene editing offers the prospect of permanent risk modification under a higher safety and evidentiary bar. Delivery innovations and multiomic‐ and imaging‐based AI further determine which endotype hypotheses can advance into scalable interventions. Together, this endotype–target–delivery logic aims to shift ASCVD care from empiric stacking toward decision pathways that are mechanistically anchored, diagnostically implementable, and clinically testable.
